A comparative study between two relaxed LMI-based fuzzy control designs

A comparative study, with theoretical analysis and digital simulations, of two conditions based on LMI for the quadratic stability of nonlinear continuous-time dynamic systems, described by Takagi-Sugeno fuzzy models, are presented. This paper shows that the methods proposed by Teixeira et. al. in 2003 provide better or at least the same results of a recent method presented in the literature. © 2005 IEEE.

Fuzzy logic to predict thermal damages of ground parts

One of the critical problems in implementing an intelligent grinding process is the automatic detection of workpiece surface burn. This work uses fuzzy logic as a tool to classify and predict burn levels in the grinding process. Based on acoustic emission signals, cutting power, and the mean-value deviance (MVD), linguistic rules were established for the various burn situations (slight, intermediate, severe) by applying fuzzy logic using the Matlab Toolbox. Three practical fuzzy system models were developed. The first model with two inputs resulted only in a simple analysis process. The second and third models have an additional MVD statistic input, associating information and precision. These two models differ from each other in terms of the rule base developed. The three developed models presented valid responses, proving effective, accurate, reliable and easy to use for the determination of ground workpiece burn. In this analysis, fuzzy logic translates the operator's human experience associated with powerful computational methods.

Three-phase four-wire circuits interpretation by means of different power theories

In order to contribute to the discussion of defining a generalized power theory, valid for unbalanced and non linear circuits, this paper discusses the relationship and discrepancies among four modern power theories. Three-phase four-wire circuits, under different conditions, have been analyzed, since the most conflicting and intriguing interpretations take place in case of return conductor occurrence. Simulation results of different load, power supply and line conditions will be discussed in order to elucidate the author's conclusions and to provoke the readers for additional discussions. © 2010 IEEE.

Estabilização de sistemas fuzzy T-S incertos usando realimenta̧ão derivativa

In some practical problems, for instance, in the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. Thus, a method for state-derivative feedback design applied to uncertain nonlinear systems is proposed in this work. The nonlinear systems are represented by Takagi-Sugeno fuzzy models during the modeling of the problem, allowing to use Linear Matrix Inequalities (LMIs) in the controller design. This type of modeling ease the control design, because, LMIs are easily solved using convex programming technicals. The control design aimed at system stabilisation, with or without bounds on decay rate. The efficiency of design procedure is illustrated through a numerical example.

Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

Characterization of the temperature, load and damage effects using piezoelectric transducer patches based on fuzzy clustering

Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in a structure. One of the critical challenges for practical implementation of SHM system is the ability to detect damage under changing environmental conditions. This paper aims to characterize the temperature, load and damage effects in the sensor measurements obtained with piezoelectric transducer (PZT) patches. Data sets are collected on thin aluminum specimens under different environmental conditions and artificially induced damage states. The fuzzy clustering algorithm is used to organize the sensor measurements into a set of clusters, which can attribute the variation in sensor data due to temperature, load or any induced damage.

VEGF-C expression in oral cancer by neurotransmitter-induced activation of beta-adrenergic receptors

The aim of this study was to investigate the expression of vascular endothelial growth factor type C (VEGF-C) in oral squamous cell carcinoma (OSCC) cell lines through norepinephrine-induced activation of beta-adrenergic receptors. Human OSCC cell lines (SCC-9 and SCC-25) expressing beta-adrenergic receptors were stimulated with different concentrations of norepinephrine (0.1, 1, and 10 μM) and 1 μM of propranolol, and analyzed after 1, 6, and 24 h. VEGF-C gene expression and VEGF-C production in the cell supernatant were evaluated by real-time PCR and by ELISA, respectively. The results showed that beta-adrenergic receptor stimulation by different concentrations of norepinephrine or blocking by propranolol did not markedly alter VEGF-C expression by SCC-9 and SCC-25 cells. VEGF-C protein levels produced by oral malignant cell lines after stimulation with different norepinephrine concentrations or blocking with propranolol was statistically similar (p > 0.05) to those of the control group (nonstimulated OSCC cell lines). Our findings suggest that stimulation of beta-adrenergic receptors by means of norepinephrine does not seem to modulate the VEGF-C expression in OSCC cell lines. These findings reinforce the need for further studies in order to understand the responsiveness of oral cancer to beta-adrenergic receptor stimulation or blockage, especially with regard to VEGF-C production. © 2012 International Society of Oncology and BioMarkers (ISOBM).

Fuzzy control embedded in microcontroller and applied to an experimental apparatus using magnetorheological fluid damper

This work focuses on applying fuzzy control embedded in microcontrollers in an experimental apparatus using magnetorheological fluid damper. The non-linear behavior of the magnetorheological dampers associated with the parametric variations on vehicle suspension models corroborate the use of the fuzzy controllers. The fundamental formulation of this controller is discussed and its performance is shown through numeric simulations. An experimental apparatus representing a two degree of freedom system containing a magnetorheological damper is used to identify the main parameters and to evaluate the performance of the closed-loop system with the embedded low-cost microcontroller-based fuzzy controller. © 2013 Brazilian Society for Automatics - SBA.

Regionalização do território de Tambaú (SP) em microbacias hidrográficas e técnicas de geoprocessamento e análise espacial como insumos a gestão governamental

Pós-graduação em Geografia - IGCE

Avaliação e treinamento de habilidades sociais de crianças em idade pré-escolar

Pós-graduação em Psicologia do Desenvolvimento e Aprendizagem - FC

Classificação da curvatura de vertentes em perfil via Thin Plate Spline e Inferência Fuzzy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Detecção e classificação de faltas de alta impedância em sistemas elétricos de potência usando lógica Fuzzy

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Previsão de cargas elétricas através de uma Rede Neural Híbrida Back-ART Fuzzy

Pós-graduação em Engenharia Elétrica - FEIS

Algoritmos para geração de referências, inicialização e proteção de um condicionador unificado de qualidade de energia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desenvolvimento de um objeto de aprendizagem para análise de sistemas de energia elétrica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)